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Intel

AI System Performance Engineer

About this role

This role sits in Intel's team that models how AI training and inference perform on GPU-based systems. The engineer builds analytical models and works with simulators to estimate end-to-end performance. Day to day, that means studying serving strategies, parallelism, collective communication and interconnect behaviour to find architectural bottlenecks. The results feed recommendations for system configurations on Intel architecture. It suits recent graduates or those with about a year of experience who have strong Python and computer architecture fundamentals and learn new tools quickly. The role is based in Bangalore with a hybrid work model.

Intel is hiring for AI System Performance Engineer, a full-time role based in Bengaluru (hybrid).

Who can apply: College grad or 1+ years. Skills: Python, GPU Architecture, LLM Workloads, Performance Modelling.

Hirastra checked that this opening is live. Apply directly through the official posting; applying is always free.

What you'll do

  • Enable new AI workloads in analytical simulators and model emerging multi-GPU deployment, parallelization and communication strategies
  • Build analytical models of proposed GPU architectures (core, memory hierarchy, training/inference scenarios) and produce performance estimates
  • Integrate and modify open-source simulators or analytical models for Intel-specific architecture
  • Run what-if sweeps over core count, memory/cache capacity and bandwidth, fabric bandwidth, GPU interconnect and deployment options
  • Deliver optimization and architecture recommendations based on the findings

What you need

  • BTech or Master's degree in Electrical Engineering, Computer Engineering, Computer Science or a related field
  • College graduate or 1+ years of experience in AI workload and GPU architecture modelling/simulation or a similar field
  • Strong Python skills, with ability to build modular, maintainable analytical models and simulation frameworks
  • In-depth understanding of computer architecture: GPU/CPU, ALU/SM core, cache, memory types and hierarchy
  • In-depth understanding of LLM AI workloads (Transformer, MoE, Attention, MLA; LLaMA, DeepSeek, Qwen, robotic workloads) and kernel internals
Location
Bengaluru
Work mode
Hybrid
Experience
College grad or 1+ years
Pay
₹12–20 LPA (Est.)
Type
Full-time job, AI & ML
Added
22 October 2026

Skills

  • Python
  • GPU Architecture
  • LLM Workloads
  • Performance Modelling

"Est." = Hirastra's estimate based on market data, not an official figure.

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